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Exploiting decentralized channel state information for random access

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2 Author(s)
S. Adireddy ; Silicon Labs., Austin, TX, USA ; L. Tong

We study the use of channel state information (CSI) for random access in fading channels. Traditionally, random access protocols have been designed by assuming simple models for the physical layer where all users are symmetric, and there is no notion of channel state. We introduce a reception model that takes into account the channel states of various users. Under the assumption that each user has access to its CSI, we propose a variant of Slotted ALOHA protocol for medium access control, where the transmission probability is allowed to be a function of the CSI. The function is called the transmission control. Assuming the finite user infinite buffer model we derive expressions for the maximum stable throughput of the system. We introduce the notion of asymptotic stable throughput (AST) that is the maximum stable throughput as the number of users goes to infinity. We consider two types of transmission control, namely, population-independent transmission control (PITC), where the transmission control is not a function of the size of the network and population-dependent transmission control (PDTC), where the transmission control is a function of the size of the network. We obtain expressions for the AST achievable with PITC. For PDTC, we introduce a particular transmission control that can potentially lead to significant gains in AST. For both PITC and PDTC, we show that the effect of transmission control is equivalent to changing the probability distribution of the channel state. The theory is then applied to code-division multiple-access (CDMA) networks with linear minimum mean-square error (LMMSE) receivers and matched filters (MF) to illustrate the effectiveness of using channel state. It is shown that through the use of channel state, with arbitrarily small power, it is possible to achieve an AST that is lower-bounded by the spreading gain of the network. This result has implications for the reachback problem in large sensor networks.

Published in:

IEEE Transactions on Information Theory  (Volume:51 ,  Issue: 2 )